Since 2010, big data has played a significant role in various fields of science, engineering and society. The paper introduces the concepts of geographic big-data, the fourth paradigm and nonlinear complex geographic system, and discusses interactive relationships of these concepts. It is proposed that geographic big-data and the fourth paradigm would become a new opportunity to research on geography complexity. Then the paper discusses how to use the methods of geographic big-data and complexity science to examine geography complexity. For example, based on big-data, a series of indicators of statistical physics fields could be constructed to describe the complex nonlinear characteristics of the real geographic world. Deep learning, complex network and multi-agent methods can be used to model and simulate the complex nonlinear geographic systems. These methods are important for a better understanding of the complexity of geographic phenomena and processes, as well as the analysis, simulation, inversion and prediction of complex geographic systems. Finally, the paper highlights that the combination of geographic big-data and complexity science would be the mainstream scientific method of geography in the 21st century.
Neil Smith is among the most renowned academics in human geography and Marxist geography. Based upon uneven development theory, Smith has integrated both the categories in Marxist theory and those in geography such as seesaw movement of the capital, spatial integration and scale evolvement to propose an approach to the even development, which has enriched Marxist geography significantly. Smith mainly reckons geographical space as a means of production, a social product and an ensemble of spatial relations. Currently, there is still a lack of overall understanding of Smith's spatial Marxist theory, though introductions to parts of his theoretic tapestry have been made. The paper summarizes Smith's spatial Marxist theory and divides it into four aspects including space production, geographical scale, American imperialism and gentrification. Thus, the paper attempts to analyze the uneven development of geographical space, to interpret the complex interactive relations among society, space and geographical scales, to illustrate the logical connections of capital seesaw movement, American imperialistic expansion and gentrification, and to end with an analysis of seesaw movement of the capital in urban scale via rent gap theory. The paper aims to offer an outline of Marxist spatial theory and geography for domestic academia, as well as theoretical and methodological inspirations for urbanization transition and economic growth in China. Smith's spatial Marxist theory is under several criticisms, to which the paper has discovered justifications. Primarily, Smith focuses on socio-spatial problems under capitalist flexible accumulation regimes, hence the accusation of spatial-temporal limitations to the explanatory power. Besides, remarks on Smith's production determinism are due to the production primacy and the effort to include political and ideological processes via cultural production inspired by Frankfurt school. Additionally, to answer queries about geographical scale, its major difference from other geographical terms is its nature as a social product that translates social divisions into spatial differentiations. Finally, Smith focuses on mediation role regarding urban ground rent to spare controversies on rent categories; hence the comment of neglecting Marxist ground rent theories. Four conclusions and policy suggestions accordingly are as follows. Firstly, high housing price is a form of secondary deprivation of labor and a potential source of social conflict in reproduction process. Long-term effective housing regulation requires public housing provision and rental right improvement. Secondly, multivariate supply of land boosts rental housing construction and meets urban dwelling needs. It may also help lower commercial housing price due to a mitigation of land scarcity. Thirdly, precautions against accumulation by dispossession of real estate developers should be taken in mature urbanized societies. Lastly, rent gap index based on price to rent ratio forecasted by hedonic price model may help stabilize housing market.
Knowledge is one of the key drivers of long-term economic growth. Additionally, it is widely accepted that not all knowledge has the same value. Nevertheless, too often in the field of economic geography and cognate, we have been obsessed with counting knowledge inputs and outputs rather than assessing the quality of knowledge produced. To fill this gap, this article focuses on the knowledge complexity and its significant role in regional innovation. To begin with, based on the "bimodal network models" of Hidalgo and Hausmann, designed to measure the complexity of knowledge, the article investigates 14349355 pieces of patent records from the State Intellectual Property Office of P.R.China to identify the technological structure of Chinese cities in terms of the patent classes between 1986 and 2015. Furthermore, the article explores the evolution of knowledge complexity in Chinese cities and how the spatial diffusion of knowledge is linked to complexity using visualizing tools such as Gephi and ArcGIS. The results show that: (1) The cities with the most complex technological structures are not necessarily those with the highest rates of patenting, which suggests that the emphasis on both quality and quantity will definitely contribute to a better understanding of the distribution of knowledge production in China; (2) Knowledge complexity is unevenly distributed across China and the evolution process shows that the hot spots are obviously southward, indicating the characteristics of geographical agglomeration and the great differences between zones; (3) More complex patents are less likely to be transferred than those with less complexity in terms of the data of patent transference and the pattern is also verified by correlational analysis, Linear Probability Model and logistic regression approach of STATA. Therefore, upgrading regional knowledge structure from low complexity to high complexity will contribute to reshaping regional advantages respectively.
By using space syntax techniques with digital historical maps in different times, this study tries to reveal the evolution process of Beijing old city's street network since the establishment of the Republic of China in the 1910s from three aspects, which are phenotype of street networks, part-whole hierarchical relation and operation efficiency. The results show that: first, the vicissitudes of dynasties divide evolution process into two parts. In the Republican Period, the street network transformed from feudal isolation structure to modern connective structure. The axisymmetric hook-ups NAIN and NACH cores patterns were broken up together. After the founding of New China in 1949, the geometry grid features of old city's street network became obvious, and the ring and big grid movement skeleton system sprang up gradually. Meanwhile, the accessibility and through frequency of different street segments became more and more similar. Second, the accessibility hierarchical relationship in each sub-area of the old city was in a constant change, however, the through frequency relationship stabilized for more than 100 years. Compared with other sub-areas, the east city had obvious spatial advantages of accessibility and through frequency. Third, two insertions of new structure and the path dependence of subsequent plan made the operation efficiency of street network experienced rise and fall. This process also emerged in east city, west city and outer city, and the stronger geometry grid feature urged east city to have a higher rising range and operation efficiency. Moreover, the imperial city's operation efficiency experienced a descent stage because of its opening wider to the outside world. In summary, this research completely organizes the phylogeny of Beijing old city's street network, provides the logical support from the street network perspective to protect the capital's traditional and inherit historical context, and expands the theoretical algorithm system of space syntax.
With the implementation of the strategy of "Going Global" and the Belt and Road Initiative, China is playing a critical role in the global economy. Along with the increasing globalization of Chinese enterprises, China has gradually become an influential force in the global market. The contemporary literature has revealed how overseas Chinese networks and communities promoted foreign investments into China in the past four decades. Whether these networks and communities can drive Chinese capital to expand overseas once again is ambiguous. Employing the classical location theory, this study examines Chinese corporate investments in Southeast Asia from 2001 to 2016. Data were collected from official information of Chinese corporations released by the Ministry of Commerce of China. This research covers 10 countries located in Southeast Asia including Malaysia, Philippines, Thailand, Singapore, Indonesia, Brunei, Vietnam, Cambodia, Myanmar and Laos. Utilizing the discrete-selection logit regression model, the study analyzed the correlation between overseas Chinese social networks and the site selection of Chinese outbound investment. The results show that: (1) overall, the positive correlation between the number of overseas Chinese in Southeast Asian countries and the location choice of Chinese outbound investment is apparently significant; (2) in terms of time sequence, the significance of the correlation is soaring up, indicating that overseas Chinese have potentials in imposing positive impact on the promotion of locational choice of Chinese enterprises while the impact is potentially on the rise; (3) as for industrial structure and corporate functions, the impact is various and significant only in some industries and corporate segments. These findings affirm the positive value of overseas Chinese social networks on the globalization of Chinese corporations. Considering the implementation of the Belt and Road Initiative, this paper suggests that Chinese government should pay more attention to the improvement of the interactions between Chinese enterprises and overseas Chinese networks.
On the basis of patent transaction data in 2015, spatial pattern of interurban technology transfer network in China was portrayed by integrating big data mining, social network, and GIS, from the perspectives of nodal strength and centrality, linkage intensity, and modular divisions. Then, its key influencing factors were identified as well using the Negative Binominal Regression Analysis. Some findings were ontained as follows. First of all, the intensity of interurban technology transfers in China is not well distributed with obvious polarization. Those cities with higher-level technology transfers are concentrated in the three urban clusters, namely, the Yangtze River Delta, the Pearl River Delta and Beijing-Tianjin-Hebei urban agglomeration. Secondly, a typical core-periphery structure with hub-and-spoke organization is evidently observed, which consists of several hubs and the majority of cities with far lower technology transfers. Beijing, Shenzhen, Shanghai and Guangzhou are acting as the pivot of the technology transfer network and playing a critical role in aggregating and dispersing technology flows. Thirdly, technology linkage intensities of urban pairs appear to be significantly uneven with hierarchies, centralizing in the three edges from Beijing to Shanghai, from Shanghai to Guangzhou and Shenzhen, and from Beijing to Guangzhou and Shenzhen, which shapes a triangle pattern. Fourthly, the technology transfer network is divided into four communities or plates, with prominent reflexivity and spillover effects, which is resulted from geographical proximity and technological complementary. Last but not least, spatial flows of technology are co-organized by a variety of spatial diffusion modes such as hierarchical diffusion, contact diffusion and leapfrog diffusion, owing to economic and administrative powers. They are greatly influenced by urban economic scale, foreign linkage, policy making, as well as multiple proximity factors related to geographical, technological, social and industrial proximities.
Poverty has long been the focus of all countries in the world. To achieve the goal of building a moderately prosperous society in all aspects, Chinese government clearly points out that all rural residents living below the current poverty line should be lifted out of poverty, and poverty should be eliminated in all poverty-stricken counties and regions by 2020. But due to the limitation of development capacity, the improvement of the new poverty standard and living standard, there will still be quite a large number of people in poverty in future and it will exist for a long time. Thus, it is of great significance to study the pattern of rural poverty and the poverty stress at county level in China and investigate anti-poverty targeting after 2020. To this end, we first analyze the mechanism of rural poverty from the perspective of man-land areal system and construct an indicator system of county development index (CDI) to characterize county poverty stress. Then the BP neural network model is applied to measure the poverty stress and identify the county that still need policy-support (CNPS) after 2020 when the goal of eliminating poverty is achieved. Results show that poverty is a manifestation of the imbalance between human system and land system, which can be measured by three aspects, i.e., human development capability, natural resource endowment and socio-economic development. The deficiency of natural resource endowments is one of the main causes of poverty, while socio-economic development and improvement of agricultural production conditions make contribution to poverty alleviation in rural areas. Human development capability, socio-economic level, natural resource endowment and comprehensive development at county level in China show a gradient decrement from the southeast coast to the northwest inland, which can be divided into three agglomerated areas by the three ladders of the terrain. More concretely, high-cold regions of Tibetan Plateau and its periphery, as well as arid areas in the west of South Xinjiang are the low-value areas of CDI. The eastern coastal areas, Sichuan Basin and the middle and lower reaches of the Yangtze River, where the natural condition is good and the level of economic development is high, are the middle-high-/high-value areas of CDI. At last, the standard deviation of CDI is applied to measure poverty stress at county level. Results show that 716 counties need to be further focused by national anti-poverty policies after 2020, most of which are distributed in the high-cold region of Tibetan Plateau, the transition zone of the three ladders and the Karst region in Southwest China. These counties can be roughly divided into four types, i.e., key aiding counties restricted by multidimensional factors (Type Ⅰ), general aiding counties restricted by human development capability (Type Ⅱ), general aiding counties restricted by both natural resource endowment and socio-economic development (Type Ⅲ), and tgeneral aiding counties restricted by both human development capability and socio-economic development (Type Ⅳ). Understanding poverty patterns and its dynamic mechanisms as well as the ways to poverty reduction in the new period can enrich the study of poverty geography.
With the shift of urban function and the upgrade of industrial structure, the floating population structure has undergone a profound change. The floating population community is pyramidally diversified and its formation mechanism is becoming increasingly complicated. Taking Beijing as the study area, and synthesizing GIS spatial analysis, mathematical statistics analysis and spatial econometric model, this paper investigates the spatial differentiation of floating population communities in Beijing. On this basis, it explores the formation mechanism of floating population communities by synthesizing community and individual factors. The results show the following: (1) Floating population communities in Beijing circle the Forbidden City and present the dual characteristics of urban and rural areas. Meanwhile, they demonstrate obvious differentiation among spatial classes. (2) The spatial differentiation of floating population communities is the combined result of the floating population's demand and housing supply, as well as the result of community and individual factors. (3) Community factors are the external driving forces of the spatial differentiation of floating population communities. Specifically, economic factors are the basic driving force; public transportation factors are the spatial leading driving force; institutional factors are the fundamental driving force; and spatial spillover effects are the dominant driving force. (4) Individual factors are the internal driving forces of the spatial differentiation of floating population communities. Specifically, the family life cycle is the direct driving force; the socio economic status is the major driving force; the migration feature is the underlying driving force; and the basic public service demand is the insensitive driving force. This study provides a scientific basis for the government's administrative and management strategy, and advances the effective and efficient transformation and upgrade of floating population communities.
The spatio-temporal characteristics of demographic distribution in China from 2000 to 2010 were analyzed systematically from the perspective of urban agglomeration, using the methods of barycenter model, spatial autocorrelation and Theil index. The 19 urban agglomerations mentioned in the country's 13th Five-Year Plan (2016-2020) are studied in this paper. Results show that the distribution center of permanent population is moving further towards the southeast where developed urban agglomerations are concentrated. Urban agglomeration is a high value area of population density and population growth, but a low value area of natural population growth. Urban agglomeration is also the most active area of China's population flow, and the effect of population space agglomeration and diffusion is also remarkable. The spatial distribution pattern of China's population is closely related to the distribution and development of urban agglomerations. Meanwhile, the development of urban agglomerations has brought a large population into urban agglomeration or its core cities, and the distribution of population in urban agglomeration has increased significantly. Because of the attraction effect of urban agglomeration on population, the geographical difference of population density in China is further expanded. The development level of urban agglomeration in China is very different, and the urban agglomeration in different stages of development show different effects of population agglomeration and diffusion. Urban agglomerations in stage of the higher development degree, mainly located in eastern coastal densely populated areas, are featured by strong demographic attractiveness, and overall population agglomeration, hence gradually form a hierarchy. At the same time, urban agglomerations in stage of the lower development degree are mainly distributed in the central and western regions, where the population is sparse, with the city being less appealing to population. These urban agglomerations present the core edge diffusion characteristic, and the urban system structure is not stable yet.
In the context of the Belt and Road Initiative, the analysis of Eurasian land and sea transport spatial equilibrium pattern which is formed on the basis of cost coopetition is an important economic and geographic topic with both theoretical and practical significance. This article takes Beijing and Berlin as destinations on the two sides of Europe-Asia and, on the basis of existing rail networks and maritime data, adopts accessibility analysis to build a land and sea transport spatial equilibrium analysis model. Using this model, this study draws balance lines for land and sea transport in Eurasia in order to clarify patterns of Eurasian land and sea transport spatial coopetition in the context of the Belt and Road Initiative. This study shows that: (1) When only transportation costs are compared, sea transport holds an absolute advantage, while the balance line for land and sea transport passes through Russia along the Baltic Sea coastal region-Kazakhstan-Turkmenistan-Tajikistan-Northwest China-Mongolia-the Russian Far East. Herein, the spatial coopetition pattern between land and sea transport divides Eurasia into an equilibrium pattern described by a 1∶2 ratio. (2) While considering time costs, balance line shifts distinctly toward coastal regions, following the route Berlin-north coast of the Black Sea-Turkey-Tibetan Plateau-Baoji, China-Da Hinggan Prefecture, China-Chumikan, Russia. Here, the coopetition pattern between land and sea transport forms a balance posture by a 1∶1 ratio. (3) The above Eurasian land and sea transport balance lines share a strong spatial similarity with the corresponding results of the geopolitical theories of land power theory and rimland theory. This indicates an inherent common regularity in Eurasian geo-economic and geopolitical spatial differentiation. On this basis, this paper proposes a spatial division scheme for Eurasian inland area (land transport advantage zone), sea area (sea transport advantage zone) and land-and-sea area. As such, a comprehensive analysis of the spatial equilibrium relationship of land and sea transport may become a new perspective for exploring geopolitical and economic spatial patterns in Eurasia, and provide a solid geoscientific basis for the implementation of the Belt and Road Initiative.
The logistics clusters are the result of concentration, scale and specialization of logistics activities, and their quantitative measurement and development evaluation provide an important foundation for improving the land use efficiency and achieving economies of scale. Taking 289 cities at prefecture-level and above as research objects, this paper collected macro statistics data of transport, postal and warehousing industry during 2000-2014, more than 290 thousand registered logistics enterprises and 170 thousand points of interest (POI) of logistics. The evolution process and spatial pattern of logistics clusters in China are explored with the methods of Location Quotient (LQ), Horizontal Cluster Location Quotient (HCLQ), Logistics Employment Density(LED) and modified Logistics Establishments' Participation (LEP). The development level, type and development mode of different types of logistics clusters are quantified. Several important findings are derived from the study. (1) The logistics clusters are mainly located on the east side of the Hu Huanyong Line, and the accumulative pattern evolves from group to block structure, which features wide coverage and high concentration. The evolution of logistics clusters has experienced two stages of fast degradation and stable change. The development degree and efficiency of logistics clusters gradually increases. (2) 21 mature logistics clusters are distributed in the core and sub-cities of the main metropolitan areas of 16 provincial-level administrative zones, conforming to the government logistics and transport planning. 43 emerging logistics clusters are distributed in 21 provincial administrative zones, and different types of cities have huge disparities which highlight the differentiation of the market behaviors and government planning among them. (3) The logistics cluster presents a differentiated development mode with the change of scales. In urban agglomeration scale, the nested "center-periphery" structures with "main nucleus-secondary cores-general nodes" are clarified. The polar nuclear development, networked and balanced development, single core and multipoint, multi-core multipoint development patterns are formed in different provincial administrative zones.
As one of the most important modern tourism destinations, cities are playing a critical role in developing agglomerated tourism elements, shaping urban leisure space and promoting urban life quality. In particular, the city tourist flow provides a key path for connections between tourism elements and spatial organization, and its influence on urban traffic organization, public service facilities and leisure tourism industry layout has also been increasing. Motivated by these observations, this paper examines spatial characteristics of inbound tourist flows from a microscopic perspective within a city. Firstly, all photos with geographical and attribute information in Beijing from 2004 to 2015 are obtained from the Flickr API interface using data mining technology. Then, a series of data cleaning methods are used to enhance initial data quality and a database is established. Finally, spatial pattern of inbound tourist flows and spatial characteristics of areas of interest (AOI) are analyzed using various methods including P-DBSCAN and Markov chain. The main results are as follows: (1) Spatial characteristics of AOI in the historic center (the region inside the 2nd Ring Road), the central urban area (the region between the 2nd and 5th ring roads) and the suburbs (the region outside the 5th Ring Road) in Beijing are significantly different: the AOI in the historic center in Beijing cover spaces of scenic spots, leisure, entertainment, restaurants, shops and other related industries, and the boundaries between AOI are unclear, with one AOI connecting to another; AOI in the central urban area are closely related to urban functional areas, and has a definite orientation of urban functions; finally, AOI in the suburbs of Beijing are consistent with the tourist attractions, with the boundaries not going beyond scenic areas. (2) The traditional, historical and cultural AOI dominate other AOI. Meanwhile, the commercial, shopping and leisure AOI as well as modern city function related AOI are becoming more and more attractive. (3) Inbound tourist flows are mainly distributed in AOI of the historical districts and the northwest and east of the central urban areas. Moreover, there is no big tourist flow between the suburban regions. Overall, the inbound tourist flow in Beijing follows a radioactive distribution pattern centered at the historic center. (4) AOI of different regions are connected with secondary tourist flows, and the inbound tourism flow in Beijing has formed a preliminary network structure.
Since they were inscribed on the World Cultural Heritage List, ancient villages in rural China, which used to be relatively stable and closed communities, have embraced economic change that happened to the ways of life for the local residents as a result of the newly introduced economy and the flood of visitors. This paper takes Diaolou complex, a UNESCO Would Heritage site in China as a case study. It is found, after a seven-year study, that there is a significant correlation between the level of tourism development and the civic participation of local village residents.
In this paper, a comparison is made between the conditions in three different ancient villages before and after they were recognized as World Cultural Heritage Sites. With a further analysis of the data provided by the current local authorities and travel agencies concerning the main sources of income and the new economic structure, we found that there are some discrepancies in tourism development among the three ancient villages. Furthermore, to provide a plausible explanation of the interaction between tourism development and the construction of local civil society and citizenship, this paper first articulates the concept of "citizenship" in the literature, and then examines the results from in-depth interviews and field researches.
It is found that tourism development does bring about citizenship, viewed as a universal value, in the three adjacent ancient villages with similar governance patterns and similar traditions. In explaining the cultivation process and transformation mechanism of citizenship in traditional Chinese societies, this paper contributes to the studies in moral geography in China.
From the post-modernist perspective, tourists tend to seek for something different, which makes the analysis of individual tourist motivation become the key point for planning and marketing tourism products. The theory of existential authenticity receiving great attention recently, is acknowledged as a suitable approach for analyzing individual tourist motivation. Based on a detailed review on the theory of authenticity, this article pointed out that efforts need to be made when we use existential authenticity to explain touristic motivation. Although in the literature, existential authenticity is connected with concepts like alienation and anxiety to formulate an explanatory mechanism for touristic function and touristic motivation on a comprehensive concept level, effects from various circumstances and environments on alienation, anxiety and authentic self are neglected and the existing mechanism cannot be used to analyze touristic motivation in segmented markets. This article first managed to take the effects from environments, resources and possibilities on self-realizatoin into account when constructing a touristic motivation framework; then it deconstructed the concept of authentic self, and separated out basic types of authentic self and conditions for realizing them; furthermore, it corresponded basic types of alienation with those of anxiety and discussed how tourism can promote the realization of authentic self; eventually, it constructed an analytical framework of tourism motivation which can be used to develop individualized tourism products and direct tourism marketing strategy.
